Information processing apparatus, information processing method, program, and imaging apparatus including optical microscope

ABSTRACT

An information processing apparatus includes an acquisition section and a correction section. The acquisition section acquires information of lightness distribution of a first image captured by an imaging section capable of capturing an image of an observed area provided on an optical path of an optical system of an optical microscope, the image of the observed area being obtained by the optical microscope, the first image being an image of the observed area in a state where no sample is placed therein, the lightness distribution resulting from the optical system of the optical microscope. The correction section corrects, based on the information of lightness distribution acquired by the acquisition section, lightness unevenness of a second image captured by the imaging section, the second image being an image of the observed area in a state where the sample is placed therein.

CROSS REFERENCES TO RELATED APPLICATIONS

The present application claims priority to Japanese Priority PatentApplication JP 2009-283342 filed in the Japan Patent Office on Dec. 14,2009, the entire content of which is hereby incorporated by reference.

BACKGROUND

The present application relates to an information processing apparatus,an information processing method, a program, and an imaging apparatusincluding an optical microscope, which process an image signal obtainedby an image sensor to thereby correct lightness distribution of anoutput image.

From the past, for example, a digital still camera including an imagesensor such as a charge-coupled device (CCD) is widely used as animaging device. When an image of an object is captured with such animaging device, a shading correction technique for correctingdistribution of lightness or luminance of the captured image is used inmany cases.

For example, Japanese Patent Application Laid-open No. 2004-200888(hereinafter, referred to as Patent Document 1) discloses the followingshading correction technique. In the technique, first, an image of acolorless subject having a high luminance level is captured as areference subject. Based on a distribution state of the luminance levelsof video signals thus obtained, correction data corresponding to adistance from the center point of a lens or a position of the lens iscreated using a mathematical expression. With this correction data, theluminance level of the video signal obtained by image-capturing iscorrected (see, for example, paragraph [0020] of Patent Document 1).

SUMMARY

For example, in a case where an image obtained by an optical microscopeis digitized, it is difficult to predict lightness unevenness of anoutput image because of a complicated magnifying optical system of themicroscope. Therefore, it is difficult to correct lightness unevennesswith use of the correction data created by the mathematical expressionas disclosed in Patent Document 1.

In view of the circumstances as described above, it is desirable toprovide an information processing apparatus, an information processingmethod, a program, an imaging apparatus including an optical microscopethat are capable of correcting lightness unevenness that is difficult tobe predicted.

According to an embodiment, there is provided an information processingapparatus including an acquisition means and a correction means.

The acquisition means acquires information of lightness distribution ofa first image captured by an imaging means capable of capturing an imageof an observed area provided on an optical path of an optical system ofan optical microscope, the image of the observed area being obtained bythe optical microscope, the first image being an image of the observedarea in a state where no sample is placed therein, the lightnessdistribution resulting from the optical system of the opticalmicroscope.

The correction means corrects, based on the information of lightnessdistribution acquired by the acquisition means, lightness unevenness ofa second image captured by the imaging means, the second image being animage of the observed area in a state where the sample is placedtherein.

In the information processing apparatus, the information of lightnessdistribution resulting from the optical system of the optical microscopeis acquired from the first image that is an image of the observed areain a state where no sample is placed therein. Based on the informationof lightness distribution, it is possible to correct the lightnessunevenness of the second image that is an image of the observed area ina state where the sample is placed therein, the lightness unevennessbeing difficult to be predicted.

The information processing apparatus may further include a storage meansfor storing the information of lightness distribution acquired by theacquisition means. In this case, the correction means may correct thelightness unevenness of the second image based on the information oflightness distribution stored by the storage means.

For example, assuming that the lightness distribution information of apredetermined observed area for which an illumination optical system orthe like is determined is stored, it is unnecessary to newly acquire thelightness distribution information when a sample is placed in theobserved area, and the lightness unevenness of the second image can becorrected based on the stored lightness distribution information. As aresult, a processing time necessary for correcting the lightnessunevenness can be shortened.

The acquisition means may acquire the information of lightnessdistribution for each first divided area obtained by dividing the firstimage into a plurality of areas. In this case, the correction means maycorrect the lightness unevenness of the second image for each seconddivided area obtained by dividing the second image into a plurality ofareas, the second divided area corresponding to the first divided area.

In the information processing apparatus, the lightness distributioninformation is acquired for each first divided area of the first image.Then, the lightness unevenness of the second image is corrected for eachsecond divided area of the second image that corresponds to the firstdivided area. As a result, a processing time necessary for correctingthe lightness unevenness can be shortened.

The acquisition means may acquire information of chromaticitydistribution of the first image, the chromaticity distribution resultingfrom the optical system of the optical microscope. In this case, thecorrection means may adjust a white balance of the second image based onthe information of chromaticity distribution acquired by the acquisitionmeans.

In the information processing apparatus, both the lightness distributioninformation and the chromaticity distribution information resulting fromthe optical system of the optical microscope can be acquired from thefirst image. As a result, the lightness unevenness of the second imagecan be corrected based on the lightness distribution information. Inaddition, the white balance of the second image can be adjusted based onthe chromaticity distribution information.

According to another embodiment, there is provided an informationprocessing method, which is executed by an information processingapparatus, as follows.

In other words, the information processing method includes: acquiringinformation of lightness distribution of a first image captured by animaging means capable of capturing an image of an observed area providedon an optical path of an optical system of an optical microscope, theimage of the observed area being obtained by the optical microscope, thefirst image being an image of the observed area in a state where nosample is placed therein, the lightness distribution resulting from theoptical system of the optical microscope; and correcting, based on theacquired information of lightness distribution, lightness unevenness ofa second image captured by the imaging means, the second image being animage of the observed area in a state where the sample is placedtherein.

According to another embodiment, there is provided a program causing aninformation processing apparatus to execute the information processingmethod described above. The program may be recorded on a recordingmedium.

According to another embodiment, there is provided an imaging apparatusincluding an optical microscope, an imaging means, an acquisition means,and a correction means.

The optical microscope includes an optical system.

The imaging means is capable of capturing an image of an observed areaprovided on an optical path of the optical system, the image of theobserved area being obtained by the optical microscope.

The acquisition means acquires information of lightness distribution ofa first image captured by the imaging means, the first image being animage of the observed area in a state where no sample is placed therein,the lightness distribution resulting from the optical system of theoptical microscope.

The correction means corrects, based on the information of lightnessdistribution acquired by the acquisition means, lightness unevenness ofa second image captured by the imaging means, the second image being animage of the observed area in a state where the sample is placedtherein.

According to another embodiment, there is provided an informationprocessing apparatus including an acquisition section and a correctionsection. The acquisition section acquires information of lightnessdistribution of a first image captured by an imaging section capable ofcapturing an image of an observed area provided on an optical path of anoptical system of an optical microscope, the image of the observed areabeing obtained by the optical microscope, the first image being an imageof the observed area in a state where no sample is placed therein, thelightness distribution resulting from the optical system of the opticalmicroscope. The correction section corrects, based on the information oflightness distribution acquired by the acquisition section, lightnessunevenness of a second image captured by the imaging section, the secondimage being an image of the observed area in a state where the sample isplaced therein.

As described above, according to an embodiment of the presentapplication, lightness unevenness resulting from an optical system of anoptical microscope, which is difficult to be predicted, can becorrected.

Additional features and advantages are described herein, and will beapparent from the following Detailed Description and the figures.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a block diagram showing a structural example of an imagingsystem including an information processing apparatus according to afirst embodiment;

FIG. 2 is a diagram schematically showing structures of an opticalmicroscope and an imaging apparatus shown in FIG. 1;

FIG. 3 is a block diagram showing a structural example of the imagingapparatus shown in FIG. 1;

FIG. 4 is a diagram schematically showing Raw data as image datagenerated by the imaging apparatus shown in FIG. 3;

FIG. 5 is a block diagram showing a structural example of a PC shown inFIG. 1;

FIG. 6 is a flowchart showing processing of the PC shown in FIG. 1;

FIG. 7 is a diagram for explaining a method for calibration processingshown in FIG. 6;

FIG. 8 is a diagram showing an example of an all-white image generatedin the calibration processing shown in FIG. 7;

FIG. 9 is a diagram for explaining a method for shading correctionprocessing shown in FIG. 6;

FIG. 10 is a diagram showing an example of a sample image that is notyet subjected to the shading correction shown in FIG. 9;

FIG. 11 is a diagram showing a sample image that has been subjected tothe shading correction shown in FIG. 9;

FIG. 12 is a flowchart showing processing of a PC as an informationprocessing apparatus according to a second embodiment;

FIG. 13 is a diagram for explaining calibration processing and autowhite balance correction processing performed by the PC of the secondembodiment; and

FIG. 14 is a diagram showing a structural example of an imaging systemaccording to other embodiments.

DETAILED DESCRIPTION

Embodiments of the present application will be described below in detailwith reference to the drawings.

First Embodiment

FIG. 1 is a block diagram showing a structural example of an imagingsystem including an information processing apparatus according to afirst embodiment. FIG. 2 is a diagram schematically showing structuresof an optical microscope and an imaging apparatus shown in FIG. 1. Animaging system 400 in FIG. 1 includes an optical microscope 300, animaging apparatus 200 as an imaging means, and a personal computer (PC)100 as an information processing apparatus. As the imaging apparatus200, for example, a digital still camera is used.

The optical microscope 300 includes, for example, a light source 301such as a light-emitting diode (LED), an illumination optical system302, an image-forming optical system 303, and a sample stage 304provided on an optical path of the illumination optical system 302 andimage-forming optical system 303. On the sample stage 304, an observedarea 306 is provided in which a sample 305 is placed, and an image ofthe observed area 306 is generated.

The imaging apparatus 200 includes, for example, an image sensor 201such as a charge-coupled device (CCD), and can capture an image of theobserved area 306 that is obtained by the optical microscope 300 andstore the image as image data. This image data is read by the PC 100 andis output after being subjected to data processing to be describedlater.

Here, the imaging apparatus 200 and the PC 100 will be described indetail.

FIG. 3 is a block diagram showing a structural example of the imagingapparatus 200. FIG. 4 is a diagram schematically showing Raw data asimage data generated by the imaging apparatus 200.

The imaging apparatus 200 includes the image sensor 201, a preprocessingcircuit 202, a recording medium interface (I/F) 203, and a recordingmedium 204. As the recording medium 204, for example, a memory card, anoptical disc, or a magnetic optical disc is used.

Incident light is collected by a lens (not shown) under predeterminedimaging-capturing conditions (aperture, zoom, focus, and the like), andan optical image is formed on an imaging surface of the image sensor201. The image sensor 201 outputs the imaged result of the optical imageformed on the imaging surface to the preprocessing circuit 202. In thisembodiment, a sensor in which color filters of G are arranged incheckered pattern is used as the image sensor 201, but a three-platesensor, a black-and-white sensor, a line sensor, or a multi-sensor maybe used, for example.

The preprocessing circuit 202 previously processes an output signal fromthe image sensor 201 and controls the recording medium I/F 203 to recorda Raw data file on the recording medium 204. As shown in FIG. 4, as Rawdata 205, a rectangular CCD image having an invalid pixel area 206 suchas optical black (OPB), a valid pixel area 207, and an effective pixelarea 208 is stored in dot sequence in the Raw data file.

[Structure of Information Processing Apparatus]

FIG. 5 is a block diagram showing a structural example of the PC 100.The PC 100 includes a CPU (Central Processing Unit) 101, a ROM (ReadOnly Memory) 102, a RAM (Random Access Memory) 103, an HDD (Hard DiskDrive) 104, an operation unit 105, a display unit 106, a recordingmedium interface (I/F) 107, a printer interface (I/F) 108, and a bus 109that connects those components above to each other.

The CPU 101 reads a system program such as an operating system (OS) fromthe ROM 102 or the like, and executes the system program using a workarea secured in the RAM 103. The CPU 101 reads an image processingprogram or the like from the ROM 102, the RAM 103, the HDD 104, or thelike, and executes the program using the work area secured in the RAM103, or a primary and/or secondary cache provided in the CPU 101.

The CPU 101 can perform, on the Raw data 205 described above, a seriesof image quality correction processing including optical correctionprocessing, gamma correction processing, demosaic processing, noisereduction processing, and the like. Further, the CPU 101 forms recordingimage data by compressing luminance data and color data by apredetermined data compression system, and restores the original Rawdata 205 that is not subjected to the data compression by decompressingthe recording image data. Here, the CPU 101 functions as a processingexecution section, a progress information management section, a resourceinformation acquisition section, a processing-priority setting section,and a processing control section.

The ROM 102 stores programs executed by the CPU 101, various types ofdata necessary for processing, and the like.

The RAM 103 includes a video RAM (VRAM) for image display (not shown),and is mainly used as a work area in which various types of processingare performed.

The HDD 104 includes a hard disk, and performs data write/read withrespect to the hard disk in accordance with the control of the CPU 101.

The operation unit 105 includes numeric keys, character keys, arrowkeys, various function keys, and the like and supplies, to the CPU 101,an operation input from a user. The operation unit 105 may include apointing device such as a mouse. The CPU 101 controls the respectiveunits to perform processing corresponding to the operation input that isinput by the user via the operation unit 105.

The display unit 106 includes a display device such as an LCD (LiquidCrystal Display) and a CRT (Cathode Ray Tube), and displays an imagecorresponding to an image signal formed based on the luminance data andcolor data.

The recording medium I/F 107 performs data write/read with respect to arecording medium 110 such as a memory card, an optical disc, and amagnetic optical disc. Alternatively, as the recording medium I/F 107and the recording medium 110, an HDD including a hard disk may be used.

The printer I/F 108 outputs printing data of the image, or the like to aprinter 111.

Operation of Information Processing Apparatus

FIG. 6 is a flowchart showing the processing of the PC 100, asinformation processing according to this embodiment. Here, a Raw datafile of a sample image as a second image is recorded in the HDD 104 ofthe PC 100 in a compressed state, the second image being an image of theobserved area 306 on which the sample 305 is placed, which is generatedby the imaging apparatus 200.

The CPU 101 of the PC 100 decompresses the Raw data file of the sampleimage that is recorded in the HDD 104. Then, the CPU 101 stores the Rawdata 205 of the sample image stored on the Raw data file in apredetermined storage area of the RAM 103 in a decompressed state.

The CPU 101 performs calibration processing in advance in accordancewith an instruction of the user or factory coordination (Step 101). Thecalibration processing refers to processing for creasing a correctiontable involving the capture of an all-white image by the imagingapparatus 200. The calibration processing will be described later indetail.

The CPU 101 performs optical correction processing on the Raw data 205of the sample image, the optical correction processing including defectcorrection, RawNR (noise reduction), and the like (Step 102). Further,the CPU 101 performs demosaic processing on the Raw data 205 of thesample image (Step 103). The demosaic processing refers to processing ofperforming RGB simultaneous processing on the Raw data 205 of the sampleimage stored in dot sequence. Hereinafter, each pixel of the sampleimage is constituted of three values of RGB at a matched position on animage space. It should be noted that in this embodiment, the processingperformed after the RGB simultaneous processing but before the shadingcorrection, such as gamma correction processing, is also included in thedemosaic processing.

The CPU 101 seeks an instruction as to whether to perform the shadingcorrection from the user via a user interface, for example (Step 104).Upon receiving an instruction to perform the shading correction from theuser, the CPU 101 performs shading correction processing based on thecorrection table obtained by the calibration processing in Step 101(Step 105). The shading correction processing refers to processing forsetting the pixels of the sample image to have appropriate lightness,which will be described later in detail.

The CPU 101 judges whether there is processing not yet completed, inaccordance with a progress flag (Step 106). Then, if there is processingnot yet completed, the CPU 101 continues the processing until theprocessing not yet completed does not exist (Step 107). In thisembodiment, all processing performed after the shading correction iscarried out in this step. The CPU 101 encodes the Raw data 205 of theprocessed sample image (Step 108), and then terminates the imageprocessing.

Calibration Processing

FIG. 7 is a diagram for explaining a method for calibration processingof Step 101 shown in FIG. 6. FIG. 8 is a diagram showing an example ofan all-white image generated in the calibration processing.

For example, assuming that the user 150 inputs an instruction of thecalibration processing via a calibration button 151 of the operationunit 105, the imaging apparatus 200 captures an all-white image (firstimage) 160 that is an image of the observed area 306 on which no sampleis placed, and generates a Raw data file of the all-white image 160. TheRaw data file of the all-white image 160 is compressed and recorded inthe HDD 104 of the PC 100 in that state. It should be noted that the Rawdata file of the all-white image 160, which is generated by the imagingapparatus 200, may be stored in the HDD 104 of the PC 100 in advance.

The CPU 101 stores the Raw data of the all-white image 160 in adecompressed state in a predetermined area of the RAM 103. Then, theoptical correction processing and demosaic processing described in Steps102 and 103 of FIG. 6 are performed on the Raw data of the all-whiteimage 160. Thus, the all-white image 160 becomes an image on which allfactors of the unevenness caused by the light source 301, theillumination optical system 302, and the image-forming optical system303, and noises that are not completely removed by the opticalcorrection processing in Step 102 are superimposed, in contrast to atheoretical white color.

The CPU 101 performs LPF (Low Pass Filter) processing on the pixels ofthe all-white image 160. The LPF processing refers to processing ofsmoothing the pixels of the all-white image 160 with pixels therearound.By the LPF processing, the noises that are not completely removed by theoptical correction processing are removed. As a result, the all-whiteimage 160 becomes an all-white image 160′ on which all factors of theunevenness caused by the light source 301, the illumination opticalsystem 302, and the image-forming optical system 303 are exclusivelysuperimposed, in contrast to a theoretical white color. It should benoted that the noise removal processing for the all-white image 160 maybe performed not by the LPF processing, but a median filter, patternrecognition, or an algorithm such as a learning circuit.

As shown in FIG. 8, in an end portion on the right-hand side in theall-white image 160′, there is a lightness uneven area A that isbrighter than other areas. Further, at the center portion of theall-white image 160′, for example, there is a lightness uneven area Bthat is generated due to dust or the like existing on the optical pathof the illumination optical system 302 or the image-forming opticalsystem 303.

The CPU 101 divides the all-white image 160′ into a plurality of firstdivided areas 161, and calculates representative lightness values R₁,G₁, B₁ as lightness distribution information for each of the firstdivided areas 161. As the representative lightness values R₁, G₁, B₁,for example, average luminance values of R, G, B in each of the firstdivided areas 161, maximum luminance values of R, G, B in each of thefirst divided areas 161, or the like are used. In addition, the CPU 101calculates average values avgR, avgG, and avgB of R, G, B in the entireframe of the all-white image 160′, as the lightness distributioninformation. Then, reciprocals KR, KG, and KB of the representativelightness values R₁, G₁, and B₁ with respect to the average values avgR,avgG, and avgB (that is, KR=avgR/R₁, KG=avgG/G₁, and KB=avgB/B₁) arecalculated, to thereby create a correction table 170. For example, theaverage values avgR, avgG, and avgB are each set to 1.0, and therepresentative lightness values R₁, G₁, B₁ with the set average valuesas references may be calculated. In this case, the correction table 170of the representative lightness values R₁, G₁, B₁ may be created, orthose of the reciprocals KR, KG, KB may be created.

The correction table 170 is recorded in the HDD 104 or the like of thePC 100, or stored in a predetermined storage area of the RAM 103. Thus,all factors of the unevenness caused by the light source 301, theillumination optical system 302, and the image-forming optical system303 in contrast to a theoretical white color are exclusively stored, asmultipliers of R, G, B for the pixels, in the HDD 104 or the like. Itshould be noted that the correction tales of the representativelightness values R1, G1, B1 may be created and stored in the HDD 104 orthe like.

For example, due to changes in intensity of the light source 301 of theoptical microscope 300 and in structure of the optical system, secularchanges, or the like, it may be necessary to update the calibrationprocessing. Also in such a case, the calibration processing describedabove is performed in response to the instruction from the user 150, forexample.

Shading Correction Processing

FIG. 9 is a diagram for explaining a method for shading correctionprocessing in Step 105 shown in FIG. 6. FIG. 10 is a diagram showing anexample of a sample image 180 that is not yet subjected to the shadingcorrection. FIG. 11 is a diagram showing a sample image 182 that hasbeen subjected to the shading correction. As shown in FIG. 10, thesample image 180 that is not yet subjected to the shading correctionincludes the lightness uneven areas A and B that are generated in theall-white image 160′ shown in FIG. 8.

The CPU 101 calculates, from the correction table 170 stored in the HDD104 or the like, a multiplier for each of R, G, B that corresponds toeach pixel of the sample image 180 as follows. The CPU 101 divides thesample image 180 into a plurality of second divided areas 181 thatcorrespond to the first divided areas 161 of the all-white image 160.Then, the luminance values of R, G, B of each pixel within a seconddivided area 181 are multiplied by the reciprocals KR, KG, KB of therepresentative lightness values R₁, G₁, B₁ of each corresponding firstdivided area 161. Thus, the lightness unevenness exclusively resultingfrom all factors of the unevenness caused by the light source 301, theillumination optical system 302, and the image-forming optical system303 in contrast to a theoretical white color are corrected for each ofthe second divided areas 181 of the sample image 180.

From the sample image 182 that have been subjected to the shadingcorrection, which is shown in FIG. 11, it is found that the lightnessuneven areas A and B generated in the sample image 180 are corrected. Itshould be noted that in an imaging optical system with a shallow depthof field that is included in the optical microscope 300, the light froma subject is not parallel due to a radiation angle of the light from thelight source 301 or an illumination diaphragm and has a certain angle,and therefore the lightness unevenness such as a colored flare andsensor shading are also caused. In addition, there may be a case wherethe lightness unevenness may occur due to a shutter speed of the imagingapparatus 200 or a temperature change of the light source 301. Suchlightness unevenness can also be corrected by the shading correctionprocessing described in this embodiment.

The light source 301 and the optical system of the optical microscope300 can be managed, and certain imaging conditions can be held in timesequence or on a space. Therefore, the shading correction processing asdescribed above can be performed based on the lightness distributioninformation obtained from the all-white image 160′.

As described above, in the PC 100 as the information processingapparatus according to this embodiment, the sample image 180 issubjected to the shading correction based on the representativelightness values R₁, G₁, B₁ and the average values avgR, avgG, and avgBthat serve as the lightness distribution information of the all-whiteimage 160′ captured by the imaging apparatus 200. Thus, it is possibleto correct lightness unevenness resulting from the optical system or thelike of the optical microscope 300, which is difficult to be predicted.As a result of this, it is possible to improve a gray scale, aresolution, a dynamic range expansion, or color reproduction, or thelike of the sample image 180.

In addition, for example, assuming that the correction table 170obtained under predetermined imaging conditions in which the lightsource 301, the illumination optical system 302, the image-formingoptical system 303, and the like are determined is stored in the HDD 104or the like, when the sample 305 is placed in the observed area 306, itis unnecessary to capture an all-white image 160 of the observed area306 again and calculate the representative lightness values R₁, G₁, B₁.In other words, it is possible to correct the lightness unevenness ofthe sample image 180 based on the correction table 170 stored in the HDD104. Thus, it is possible to shorten a processing time necessary for thecorrection of the lightness unevenness.

The correction table 170 may be loaded in accordance with theinstruction of the user 150 or may be loaded automatically. For example,in a case where the area of the sample 305 is larger than that of theobserved area 306, a plurality of sample images 180 is captured. At thistime, if the correction table 170 is automatically loaded each time onesample image 180 is captured, the convenience of the user 150 isenhanced. The plurality of sample images 180 is subjected to the shadingcorrection processing described above, with the result that an image ofthe sample 305 that does not cause a feeling of strangeness can beobtained by bonding a plurality of sample images 182 in which lightnessunevenness is corrected.

In addition, in this embodiment, the representative lightness values R1,G1, B1 are calculated for each of the first divided areas 161 of theall-white image 160′, and the lightness unevenness is corrected for eachsecond divided area 181 corresponding to the first divided area 161.Thus, for example, even in a case where the Raw data 205 having a largesize of, for example, 10 MB per image is processed, the loads on theprocessing resources such as the CPU 101 and the RAM 103 of the PC 100are alleviated and a processing speed can be constantly improved.

Second Embodiment

An information processing apparatus according to a second embodimentwill be described. In the following description, equivalents to variousapparatuses or data used in the imaging system 400 described in thefirst embodiment are not descried or simply described.

In the information processing apparatus (PC) of this embodiment, inaddition to the shading correction processing described in the firstembodiment, auto white balance (AWB) correction processing can beperformed on the sample image. The auto white balance correctionprocessing refers to processing of automatically judging an area to bewhite in the sample image and correcting the luminance values of R, G, Bof the sample image so that the area to be white is changed to be white.

In the auto white balance correction processing that is known from thepast, image data of a target image is detected. The detection refers toprocessing of performing metering by a metering technique that isadaptive to a subject, and calculating an appropriate white balance gainvalue by using a statistical technique such as a histogram. Based on thewhite balance gain value, a white balance of the target image isadjusted.

[Operation of Information Processing Apparatus]

FIG. 12 is a flowchart showing processing of a PC as the informationprocessing apparatus according to this embodiment. FIG. 13 is a diagramfor explaining the calibration processing and the auto white balancecorrection processing performed by the PC of this embodiment.

Calibration Correction Processing

In Step 201 shown in FIG. 12, the calibration processing is performed asfollows. First, as described in the first embodiment, the CPU of the PCcalculates representative lightness values R₁, G₁, B₁ as lightnessdistribution information for each of the first divided areas 161 of theall-white image 160. In addition, the CPU calculates average valuesavgR, avgG, and avgB of R, G, B in the entire frame of the all-whiteimage 160, as lightness distribution information. Then, reciprocals KR,KG, and KB of the representative lightness values R₁, G₁, and B₁ withrespect to the average values avgR, avgG, and avgB (that is, KR=avgR/R₁,KG=avgG/G₁, and KB=avgB/B₁) are calculated, to thereby create acorrection table.

Then, the CPU calculates multipliers AWB_R and AWB_B for the auto whitebalance correction. Those multipliers AWB_R and AWB_B are represented bythe following expressions.AWB_(—) R=avgG/avgRAWB_(—) B=avgG/avgB

In other words, the CPU utilizes the average values avgR, avgG, and avgBcalculated for the shading correction processing as chromaticitydistribution information for the auto white balance correctionprocessing. Thus, a memory usage and a processing time can be reduced.

The CPU creates a correction table of the calculated multipliers AWB_Rand AWB_B. Alternatively, AWB_R and AWB_B may be appropriatelycalculated based on the correction table of the reciprocals KR, KG, KBwhen needed.

The operation performed from Step 202 to Step 204 is the same as thatfrom Step 102 to Step 104 of the flowchart shown in FIG. 6, andtherefore description thereof will be omitted.

In Step 205, the reciprocals KR, KG, KB calculated in the calibrationprocessing described above are used for performing shading correctionprocessing on the sample image 180. Thus, a sample image 182 in whichlightness unevenness is corrected is created.

The CPU of the PC seeks an instruction as to whether to perform the autowhite balance correction via a user interface, for example (Step 206).Upon receiving an instruction to perform the auto white balancecorrection, the CPU performs auto white balance correction processing asfollows, based on the correction table calculated by the calibrationprocessing in Step 201 (Step 207).

Auto White Balance Correction Processing

The CPU multiplies a luminance value of R of each pixel of the sampleimage 182 by AWB_R, and multiplies a luminance value of B of each pixelby AWB_B. Thus, a sample image 183 in which a white balance is adjustedis created. The multipliers AWB_R and AWB_B contain all spectralcharacteristics of the light source, the illumination optical system,and the image-forming optical system in contrast to a theoretical whitecolor. Therefore, the sample image 183 becomes an image in which allspectral characteristics of the light source, the illumination opticalsystem, and the image-forming optical system are corrected so that atheoretical white becomes white.

Heretofore, in the PC according to this embodiment, both the lightnessdistribution information for shading correction processing and thechromaticity distribution information for auto white balance correctionprocessing are acquired from the all-white image 160 captured by theimaging apparatus. Thus, it is possible to acquire the chromaticitydistribution information in the calibration processing in Step 201 shownin FIG. 12. Further, it becomes unnecessary to detect Raw data of thesample image 182 as in the case of the past. Accordingly, a memory usageand a processing time can be largely reduced.

It should be noted that in this embodiment, one of the auto whitebalance correction processing described above and white balancecorrection processing set by the user 150 can be selected by the user150. Alternatively, preset white balance correction processing may beselected. As shown in FIG. 13, the user 150 appropriately sets the whitebalance correction processing via, for example, a white balance button188 of the operation unit. Alternatively, one of the white balancecorrection processing that are described above is selected. With aswitching block 189, the white balance correction processing performedon the sample image 182 is switched in accordance with the instructionof the user 150.

The information processing apparatus according to each of theembodiments described above is used in a system that digitizes an imageof a cell, a tissue, an organ, or the like of a living body, which iscaptured by the optical microscope, in the field of medicine orpathology, for example, to examine the tissue or the like by a doctor ora pathologist or diagnose a patient based on the digitized image.However, the information processing apparatus may be applicable to otherfields in addition to this field.

Other Embodiments

Embodiments according to the present application are not limited to theembodiments described above, and other various embodiments may bepossible.

In the embodiments described above, the PC is exemplified as theinformation processing apparatus. However, for example, by the imagingapparatus 200 shown in FIG. 1, part or all of the calibrationprocessing, the shading correction processing, or the auto white balancecorrection processing may be performed. In this case, the imagingapparatus 200 and the PC 100 are used as the information processingapparatus according to an embodiment. Further, for example, a scannerapparatus having a function of an optical microscope may be used as animaging apparatus including an optical microscope according to anembodiment, the imaging apparatus having the functions of the opticalmicroscope 300, the imaging apparatus 200, and the PC 100 shown in FIG.1.

In addition, as shown in FIG. 14, the Raw data of the all-white image orsample image generated by a scanner apparatus 500 used as an embodimentmay be stored in a computer different from the PC 100 or the server 600,and the PC 100 that the user uses as a terminal apparatus may receivethat Raw data by accessing those different computer and server 600. Inthis case, the PC 100 and the server 600 serving as terminal apparatusesmay be connected via a network 700 such as LAN (Local Area Network) andWAN (Wide Area Network). Particularly, the telepathology or remotediagnosis can be realized with use of WAN.

In the description above, the Raw data file containing the Raw data ofthe all-white image and the sample image is created by the imagingapparatus 200 shown in FIG. 3. However, the Raw data may be subjected toimage processing by the imaging apparatus 200, or a Raw data filecontaining various types of data such as information that identifies theimaging apparatus 200 and information that specifies image-capturingconditions may be created. Further, those various types of data may beused in the calibration correction processing, the shading correctionprocessing, or the auto white balance correction processing.

In the description above, as shown in FIG. 9, the all-white image 160 isdivided into the plurality of first divided areas 161, and therepresentative lightness values R1, G1, B1 are calculated for each ofthe first divided areas 161. However, the all-white image 160 may not bedivided into a plurality of areas and the luminance values of R, G, Bfor each pixel of the all-white image 160 may be calculated. Then, usingthe calculated luminance values of each pixel, the shading correctionprocessing or the like may be performed for each pixel of the sampleimage 180.

In the description above, the calibration processing is performed inadvance. However, part or all of the calibration processing may beperformed simultaneously with the shading correction processing or theauto white balance correction processing.

In the description above, the calibration processing, the shadingcorrection processing, and the auto white balance correction processingare performed after the optical correction processing and the demosaicprocessing. However, part or all of the calibration processing, theshading correction processing, or the auto white balance correctionprocessing may be performed before the optical correction processing andthe demosaic processing.

In the description above, the values of the correction table created inthe calibration processing are multipliers with respect to an idealwhite color for each pixel of the all-white image. However, the valuesmay be differences with respect to the ideal white color for each pixel.Further, the values may be first-order approximation or second-orderapproximation with respect to the ideal white color for each pixel.

In the description above, the representative lightness values R1, G1, B1and the average values avgR, avgG, and avgB are calculated as thelightness distribution information of the all-white image, and theaverage values avgR, avgG, and avgB are utilized as the chromaticitydistribution information, though not limited thereto. The informationrelated to lightness, luminance, chromaticity, color difference, or thelike obtained from the Raw data of the all-white image may be used asthe lightness distribution information and the chromaticity distributioninformation. In addition, the correction table created in thecalibration processing is not limited to the correction table of thereciprocals KR, KG, KB of the representative lightness values R1, G1, B1with respect to the average values avgR, avgG, and avgB. For example, acorrection table of RGrGbB corresponding to a color filter of the imagesensor may be created.

Further, a correction table may be created in the calibration processingeach time a Z position, an imaging position with respect to an observedarea, an illumination optical system, an image-forming optical system, asample, a sensor, an imaging apparatus, an image processing method,temperature, a field stop, an exposure time, an analog gain settingvalue, an exposure correction setting value, a chroma setting value, amagnification setting value, or the like is changed.

Further, the Raw data of each image, the correction table, or the sampleimage that has been subjected to the shading correction processingdescribed above may be used for obtaining statistical data used at atime of the calibration processing, the shading correction processing,or the auto white balance correction processing.

In the description above, the image of an observed area of the opticalmicroscope in which no sample is placed is described as an all-whiteimage. However, the color of illumination light emitted from the opticalsystem of the optical microscope is not limited to white. For example,80% of illumination light may be gray. In addition, an all-white imagemay be captured so that ideal shading characteristics are obtained.

It should be understood that various changes and modifications to thepresently preferred embodiments described herein will be apparent tothose skilled in the art. Such changes and modifications can be madewithout departing from the spirit and scope and without diminishing itsintended advantages. It is therefore intended that such changes andmodifications be covered by the appended claims.

The application is claimed as follows:
 1. An information processingapparatus, comprising: an acquisition means for acquiring infoiinationof lightness distribution of a first image captured by an imaging meanscapable of capturing an image of an observed area provided on an opticalpath of an optical system of an optical microscope, the image of theobserved area being obtained by the optical microscope, the first imagebeing an image of the observed area in a state where no sample is placedtherein, the lightness distribution resulting from the optical system ofthe optical microscope; and a correction means for correcting, based onthe information of lightness distribution acquired by the acquisitionmeans, lightness unevenness of a second image captured by the imagingmeans, the second image being an image of the observed area in a statewhere the sample is placed therein.
 2. The information processingapparatus according to claim 1, further comprising a storage means forstoring the information of lightness distribution acquired by theacquisition means, wherein the correction means corrects the lightnessunevenness of the second image based on the information of lightnessdistribution stored by the storage means.
 3. The information processingapparatus according to claim 1, wherein the acquisition means acquiresthe information of lightness distribution for each first divided areaobtained by dividing the first image into a plurality of areas, whereinthe correction means corrects the lightness unevenness of the secondimage for each second divided area obtained by dividing the second imageinto a plurality of areas, the second divided area corresponding to thefirst divided area.
 4. The information processing apparatus according toclaim 1, wherein the acquisition means acquires information ofchromaticity distribution of the first image, the chromaticitydistribution resulting from the optical system of the opticalmicroscope, wherein the correction means adjusts a white balance of thesecond image based on the information of chromaticity distributionacquired by the acquisition means.
 5. An information processing method,which is executed by an information processing apparatus, theinformation processing method comprising: acquiring information oflightness distribution of a first image captured by an imaging meanscapable of capturing an image of an observed area provided on an opticalpath of an optical system of an optical microscope, the image of theobserved area being obtained by the optical microscope, the first imagebeing an image of the observed area in a state where no sample is placedtherein, the lightness distribution resulting from the optical system ofthe optical microscope; and correcting, based on the acquiredinformation of lightness distribution, lightness unevenness of a secondimage captured by the imaging means, the second image being an image ofthe observed area in a state where the sample is placed therein.
 6. Anon-transitory computer readable medium storing a computer programcausing an information processing apparatus to execute: acquiringinformation of lightness distribution of a first image captured by animaging means capable of capturing an image of an observed area providedon an optical path of an optical system of an optical microscope, theimage of the observed area being obtained by the optical microscope, thefirst image being an image of the observed area in a state where nosample is placed therein, the lightness distribution resulting from theoptical system of the optical microscope; and correcting, based on theacquired information of lightness distribution, lightness unevenness ofa second image captured by the imaging means, the second image being animage of the observed area in a state where the sample is placedtherein.
 7. An imaging apparatus, comprising: an optical microscopeincluding an optical system; an imaging means capable of capturing animage of an observed area provided on an optical path of the opticalsystem, the image of the observed area being obtained by the opticalmicroscope; an acquisition means for acquiring information of lightnessdistribution of a first image captured by the imaging means, the firstimage being an image of the observed area in a state where no sample isplaced therein, the lightness distribution resulting from the opticalsystem of the optical microscope; and a correction means for correcting,based on the information of lightness distribution acquired by theacquisition means, lightness unevenness of a second image captured bythe imaging means, the second image being an image of the observed areain a state where the sample is placed therein.
 8. An informationprocessing apparatus, comprising: an acquisition section to acquireinformation of lightness distribution of a first image captured by animaging section capable of capturing an image of an observed areaprovided on an optical path of an optical system of an opticalmicroscope, the image of the observed area being obtained by the opticalmicroscope, the first image being an image of the observed area in astate where no sample is placed therein, the lightness distributionresulting from the optical system of the optical microscope; and acorrection section to correct, based on the information of lightnessdistribution acquired by the acquisition section, lightness unevennessof a second image captured by the imaging section, the second imagebeing an image of the observed area in a state where the sample isplaced therein.